Reverse Genetics of Sorghum

Project aims to develop reverse genetics resources for sorghum, including a large mutant population and a Natural Diversity Library (DNA of a world-representative sorghum germplasm sub-set). Additionally, inter specific wide crosses will be studied.

A genome-wide association study of Cloninger's temperament scales: implications for the evolutionary genetics of personality

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

The shared genetics of migraine and anxious depression

OBJECTIVES To investigate: - (1) whether shared genetic factors influence migraine and anxious depression; - (2) whether the genetic architecture of migraine depends on anxious depression; - (3) whether the association between migraine and anxious depression is causal. BACKGROUND Migraine and anxious depression frequently occur together, but little is known about the mechanisms causing this association. METHODS A twin study was conducted to model the genetic architecture of migraine and anxious depression and the covariance between them. Anxious depression was also added to the model as a moderator variable to examine whether anxious depression affects the genetic architecture of migraine. Causal models were explored with the co-twin control method. RESULTS Modest but significant phenotypic (rP=0.28), genetic (rG=0.30), and nonshared environmental (rE=0.26) correlations were found between the 2 traits. Interestingly, the heritability of migraine depended on the level of anxious depression: the higher the anxious depression score, the lower the relative contribution of genetic factors to the individual differences in migraine susceptibility. The observed risk patterns in discordant twins are most consistent with a bidirectional causal relationship. CONCLUSIONS These findings confirm the genetic association between migraine and anxious depression and are consistent with a syndromic association between the 2 traits. This highlights the importance of taking comorbidity into account in genetic studies of migraine, especially in the context of selection for large-scale genotyping efforts. Genetic studies may be most effective when migraine with and without comorbid anxious depression are treated as separate phenotypes.

Genetic influences on handedness: data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

Molecular genetics of primary open angle glaucoma and exfoliation syndrome

Glaucoma is the second leading cause of blindness worldwide. It is a group of optic neuropathies, characterized by progressive optic nerve degeneration, excavation of the optic disc due to apoptosis of retinal ganglion cells and corresponding visual field defects. Open angle glaucoma (OAG) is a subtype of glaucoma, classified according to the age of onset into juvenile and adult- forms with a cut-off point of 40 years of age. The prevalence of OAG is 1-2% of the population over 40 years and increases with age. During the last decade several candidate loci and three candidate genes, myocilin (MYOC), optineurin (OPTN) and WD40-repeat 36 (WDR36), for OAG have been identified. Exfoliation syndrome (XFS), age, elevated intraocular pressure and genetic predisposition are known risk factors for OAG. XFS is characterized by accumulation of grayish scales of fibrillogranular extracellular material in the anterior segment of the eye. XFS is overall the most common identifiable cause of glaucoma (exfoliation glaucoma, XFG). In the past year, three single nucleotide polymorphisms (SNPs) on the lysyl oxidase like 1 (LOXL1) gene have been associated with XFS and XFG in several populations. This thesis describes the first molecular genetic studies of OAG and XFS/XFG in the Finnish population. The role of the MYOC and OPTN genes and fourteen candidate loci was investigated in eight Finnish glaucoma families. Both candidate genes and loci were excluded in families, further confirming the heterogeneous nature of OAG. To investigate the genetic basis of glaucoma in a large Finnish family with juvenile and adult onset OAG, we analysed the MYOC gene in family members. Glaucoma associated mutation (Thr377Met) was identified in the MYOC gene segregating with the disease in the family. This finding has great significance for the family and encourages investigating the MYOC gene also in other Finnish OAG families. In order to identify the genetic susceptibility loci for XFS, we carried out a genome-wide scan in the extended Finnish XFS family. This scan produced promising candidate locus on chromosomal region 18q12.1-21.33 and several additional putative susceptibility loci for XFS. This locus on chromosome 18 provides a solid starting point for the fine-scale mapping studies, which are needed to identify variants conferring susceptibility to XFS in the region. A case-control and family-based association study and family-based linkage study was performed to evaluate whether SNPs in the LOXL1 gene contain a risk for XFS, XFG or POAG in the Finnish patients. A significant association between the LOXL1 gene SNPs and XFS and XFG was confirmed in the Finnish population. However, no association was detected with POAG. Probably also other genetic and environmental factors are involved in the pathogenesis of XFS and XFG.

Genetics of Cardiovascular Disease: A Candidate Gene Study of USF1

Cardiovascular diseases (CVD) are major contributors to morbidity and mortality worldwide. Several interacting environmental, biochemical, and genetic risk factors can increase disease susceptibility. While some of the genes involved in the etiology of CVD are known, many are yet to be discovered. During the last few decades, scientists have searched for these genes with genome-wide linkage and association methods, and with more targeted candidate gene studies. This thesis investigates variation within the upstream transcription factor 1 (USF1) gene locus in relation to CVD risk factors, atherosclerosis, and incidence and prevalence of CVD. This candidate gene was first identified in Finnish families ascertained for familial combined hyperlipidemia, a common dyslipidemia predisposing to coronary heart disease. The gene is a ubiquitously expressed transcription factor regulating expression of several genes from lipid and glucose metabolism, inflammation, and endothelial function. First, we examined association between USF1 variants and several CVD risk factors, such as lipid phenotypes, body composition measures, and metabolic syndrome, in two prospective population cohorts. Our data suggested that USF1 contributes to these CVD risk factors at the population level. Notably, the associations with quantitative measurements were mostly detected among study subjects with CVD or metabolic syndrome, suggesting complex interactions between USF1 effects and the pathophysiological state of an individual. Second, we investigated how variation at the USF1 locus contributes to atherosclerotic lesions of the coronary arteries and abdominal aorta. For this, we used two study samples of middle-aged men with detailed measurements of atherosclerosis obtained in autopsy. USF1 variation significantly associated with areas of several types of lesions, especially with calcification of the arteries. Next, we tested what effect the USF1 risk variants have on sudden cardiac death and incidence of CVD. The atherosclerosis-associated risk variant increased the risk of sudden cardiac death of the same study subjects. Furthermore, USF1 alleles associated with incidence of CVD in the Finnish population follow-up cohorts. These associations were especially prominent among women, suggesting a sex specific effect, which has also been detected in subsequent studies. Finally, as some of the low-yield DNA samples of the Finnish follow-up study cohort needed to be whole-genome amplified (WGA) prior to genotyping, we evaluated whether the produced WGA genotypes were of good quality. Although the samples giving genotype discrepancies could not be detected before genotyping with standard laboratory quality control methods, our results suggested that enhanced quality control at the time of the genotyping could identify such samples. In addition, combining two WGA reactions into one pooled DNA sample for genotyping markedly reduced the number of discrepancies and samples showing them. In conclusion, USF1 seems to have a role in the etiology of CVD. Additional studies are warranted to identify functional variants and to study interactions between USF1 and other genetic or environmental factors. This USF1 study, and other studies with low DNA yield of some samples, can benefit from whole genome amplification of the low-yield samples prior to genotyping. Careful quality control procedures are, however, needed in WGA genotyping.

Portrait of George Louis Wolff (Gerd Ludwig Wolff) holding a mouse in his genetics laboratory; Little Rock, Arkansas.

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Molecular genetics and evolution of Puumala hantavirus

Puumala virus (PUUV) is the causative agent of nephropathia epidemica (NE), a mild form of hemorrhagic fever with renal syndrome. Finland has the highest documented incidence of NE with around 1000 cases diagnosed annually. PUUV is also found in other Scandinavian countries, Central Europe and the European part of Russia. PUUV belongs to the genus Hantavirus in the family Bunyaviridae. Hantaviruses are rodent-borne viruses each carried by a specific host that is persistently and asymptomatically infected by the virus. PUUV is carried by the bank voles (Myodes glareolus, previously known as Clethrionomys glareolus). Hantaviruses have co-evolved with their carrier rodents for millions of years and these host animals are the evolutionary scene of hantaviruses. In this study, PUUV sequences were recovered from bank voles captured in Denmark and Russian Karelia to study the evolution of PUUV in Scandinavia. Phylogenetic analysis of these strains showed a geographical clustering of genetic variants following the presumable migration pattern of bank voles during the recolonization of Scandinavia after the last ice age approximately 10 000 years ago. The currently known PUUV genome sequences were subjected to in-depth phylogenetic analyses and the results showed that genetic drift seems to be the major mechanism of PUUV evolution. In general, PUUV seems to evolve quite slowly following a molecular clock. We also found evidence for recombination in the evolution of some genetic lineages of PUUV. Viral microevolution was studied in controlled virus transmission in colonized bank voles and changes in quasispecies dynamics were recorded as the virus was transmitted from one animal to another. We witnessed PUUV evolution in vivo, as one synonymous mutation became repeatedly fixed in the viral genome during the experiment. The detailed knowledge on the PUUV diversity was used to establish new sensitive and specific detection methods for this virus. Direct viral invasion of the hypophysis was demonstrated for the first time in a lethal case of NE. PUUV detection was done by immunohistochemistry, in situ hybridization and RT-nested-PCR of the autopsy tissue samples.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

Association genetics in Corymbia citriodora subsp variegata identifies single nucleotide polymorphisms affecting wood growth and cellulosic pulp yield

Wood is an important biological resource which contributes to nutrient and hydrology cycles through ecosystems, and provides structural support at the plant level. Thousands of genes are involved in wood development, yet their effects on phenotype are not well understood. We have exploited the low genomic linkage disequilibrium (LD) and abundant phenotypic variation of forest trees to explore allelic diversity underlying wood traits in an association study. Candidate gene allelic diversity was modelled against quantitative variation to identify SNPs influencing wood properties, growth and disease resistance across three populations of Corymbia citriodora subsp. variegata, a forest tree of eastern Australia. Nine single nucleotide polymorphism (SNP) associations from six genes were identified in a discovery population (833 individuals). Associations were subsequently tested in two smaller populations (130160 individuals), validating our findings in three cases for actin 7 (ACT7) and COP1 interacting protein 7 (CIP7). The results imply a functional role for these genes in mediating wood chemical composition and growth, respectively. A flip in the effect of ACT7 on pulp yield between populations suggests gene by environment interactions are at play. Existing evidence of gene function lends strength to the observed associations, and in the case of CIP7 supports a role in cortical photosynthesis.